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The Prediction of Industrial Accident Rate in Korea: A Time Series Analysis

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KMID : 1003720160250010065
ÃÖÀº¼÷:Choi Eun-Sook
Àü°æ¼÷:Jeon Gyeong-Suk/ÀÌ¿ø±â:Lee Won-Kee/±è¿µ¼±:Kim Young-Sun

Abstract

¿¬±¸¸ñÀû: º» ¿¬±¸´Â ÇâÈÄ ¡®»êÀ縸ÀÎÀ²¡¯°ú ¡®¾÷¹«»óºÎ»ó»ç¸Á10¸¸ÀÎÀ²¡¯À» ¿¹ÃøÇÏ°í ÀÌ·¯ÇÑ ¿¹ÃøÀ» °¡Àå Àß ¹Ý¿µÇÏ´Â »çȸ¡¤°æÁ¦¡¤³ëµ¿ ÁöÇ¥¸¦ È®ÀÎÇÏ°íÀÚ ½Ç½ÃµÇ¾ú´Ù.

¿¬±¸¹æ¹ý: Çѱ¹»ê¾÷¾ÈÀüº¸°Ç°ø´Ü »êÀçÅë°èºÐ¼®½Ã½ºÅÛÀÇ 2001³â¢¦2014³â »ê¾÷ÀçÇØÅë°èÀڷḦ È°¿ëÇÏ¿´À¸¸ç »ê¾÷ÀçÇØÀÇ ¿¹Ãø¿äÀÎÀÎ »çȸ¡¤°æÁ¦, ³ëµ¿·Â ±¸Á¶, ±Ù·ÎÁ¶°Ç, »ê¾÷ÀçÇØ Á¤Ã¥°ü·Ã ÁÖ¿ä ÁöÇ¥´Â ¹®Çå°íÂû ¹× Àü¹®°¡ ÀÚ¹®À» ÅëÇØ ¼±Á¤ÇÏ¿´´Ù. »ê¾÷ÀçÇØ ¹ß»ýÀ» ¿¹ÃøÇϱâ À§ÇÏ¿© ½Ã°è¿­ºÐ¼®À» È°¿ëÇÏ¿´À¸¸ç »ê¾÷ÀçÇع߻ý¿¡ ¿µÇâÀ» ¹ÌÄ¡´Â ½Ã°£ Áö¼ö¿¡ µû¸¥ ½Ã°è¿­¸ðÇüÀº ¿¬µµº¯¼ö¿Í ÇÔ²² µ¶¸³º¯¼ö¸¦ Çϳª¾¿ Ãß°¡ÇÏ¿© ¸ðÇüÀûÇÕµµ¸¦ Æò°¡ÇÏ¿´´Ù.

¿¬±¸°á°ú: ¡®»êÀ縸ÀÎÀ²¡¯°ú ¡®¾÷¹«»óºÎ»ó»ç¸Á10¸¸ÀÎÀ²¡¯ÀÌ ¼±ÇüÀû °¨¼ÒÃß¼¼¸¦ º¸À̸鼭 ±Þ°ÝÈ÷ ÁÙ¾îµé¾ú´Ù. 2001³âµµ¿¡ ºñ±³ÇÏ¿© 2014³âµµ¿¡ À̸£·¯ »êÀ縸ÀÎÀ²Àº ¸¸¸í´ç 77.0¸í¿¡¼­ 53.3¸íÀ¸·Î 30.8% ÁÙ¾îµé¾úÀ¸¸ç 2017³âµµ¿¡´Â ¸¸¸í´ç 50¡­51¸í Á¤µµ·Î °¨¼ÒÇÒ °ÍÀ¸·Î ¿¹ÃøµÇ¾ú´Ù. ¾÷¹«»óºÎ»ó»ç¸Á10¸¸ÀÎÀ²Àº 12.3¸í(2001³â)¿¡¼­ 5.8¸í(2014³â)À¸·Î 52.8% ±Þ°ÝÈ÷ ÁÙ¾î 2017³â¿¡ À̸£¸é 4.5¸í Á¤µµ·Î ³·¾ÆÁö´Â °ÍÀ¸·Î ¿¹ÃøµÇ¾ú´Ù. ¡®»êÀ縸ÀÎÀ² ¿¹Ãø¡¯À» À§Çؼ­´Â ¡®45-49¼¼ °æÁ¦È°µ¿Âü°¡À²¡¯ÀÌ, ¡®¾÷¹«»óºÎ»ó»ç¸Á 10¸¸ÀÎÀ²¡¯Àº ¡®¼Ò±Ô¸ð »ç¾÷Àå Áö¿ø»ç¾÷ ¿¹»ê¡¯ÀÌ ´Ù¸¥ Áö¼öµé°ú ºñ±³ÇÏ¿© Åë°èÀûÀ¸·Î ¿ì¼± °í·ÁÇؾßÇÒ »êÀç ¿¹Ãø ÁöÇ¥¿´´Ù.

°á·Ð: »êÀ縸ÀÎÀ² ¹× ¾÷¹«»óºÎ»ó»ç¸Á10¸¸ÀÎÀ²ÀÇ ¿¹¹æ ¹× °¨¼Ò¸¦ À§ÇØ 40´ë °æÁ¦È°µ¿Àα¸ÀÇ °í¿ë¾ÈÁ¤Á¤Ã¥°ú 20-30´ë ±Ù·ÎÀÚÀÇ ¾÷¹«¼÷·Ã ÁöÇâÀû ±Ù·ÎÁ¶°Ç ¹× ȯ°æ°³¼±ÀÌ ÇÊ¿äÇÏ¸ç ¼Ò±Ô¸ð»ç¾÷ÀåÀÇ ±Ù·Îȯ°æ ¾ÈÀüÀ» À§ÇÑ Áö¿ø È®´ë°¡ ¿ä±¸µÈ´Ù

Purpose: The purpose of this study is to predict industrial accident rate using time series analysis.

Methods: The rates of industrial accident and occupational injury death were analyzed using industrial accident statistics analysis system of the Korea Occupational Safety and Health Agency from 2001 to 2014. Time series analysis was done using the most recent data, such as raw materials of Economically Active Population Survey, Economic Statistics System of the Bank of Korea, and e-National indicators. The best-fit model with time series analysis to predict occupational injury was developed by identifying predictors when the value of Akaike Information Criteria was the lowest point. Variables into the model were selected through a series of expertises¡¯ consultations and literature review, which consisted of socioeconomic structure, labor force structure, working conditions, and occupational accidents.

Results: Indexes at the meso- and macro-levels predicting well occurrence of occupational accidents and occupational injury death were labor force participation rate for ages 45-49 and budget for small scaled workplace support. The rates of industrial accident and occupational injury death are expected to decline.

Conclusion: For reducing industrial accident continuously, we call for safe employment policy of economically active middle aged adults and support for improving safety work environment of small sized workplace.
KeyWords
»ê¾÷ÀçÇØ, ½Ã°è¿­ºÐ¼®
Industrial accident, Time series analysis
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ÇмúÁøÈïÀç´Ü(KCI)